The overall performance of the search algorithms used, as well as the structures used for knowledge representation, is important to be mindful of since the FOON can possibly be generalized for use with other objects. When dealing with tasks where the objects involved are familiar, the performance of the knowledge retrieval process is not as critical. However, if the goal is to generalize the FOON beyond the kitchen and apply it to other objects, performance becomes more important. Paulius et al. explore this more in depth by looking at situations where the universal FOON does not contain information about an object in a specific state [1]}. This leads to a situation where the task tree retrieval process is halted and cannot achieve the desired goal. Instead, the idea would be to use the limited knowledge contained in a FOON to transfer knowledge from one item to another. After exploring two different means of generalization, they concluded that there would need to be developments in how the robot interacts with items by specifying how objects should be used to solve a given task.
